Dataset Information

An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

ABSTRACT: The rapid development of high-performance technologies has greatly promoted studies of molecular oncology producing large amounts of data. Even if these data are publicly available, they need to be processed and studied to extract information useful to better understand mechanisms of pathogenesis of complex diseases, such as tumors. In this article, we illustrated a procedure for mining biologically meaningful biomarkers from microarray datasets of different tumor histotypes. The proposed methodology allows to automatically identify a subset of potentially informative genes from microarray data matrices, which differs either in the number of rows (genes) and of columns (patients). The methodology integrates nonnegative matrix factorization method, a functional enrichment analysis web tool with a properly designed gene extraction procedure to allow the analysis of omics input data with different row size. The proposed methodology has been used to mine microarray of solid tumors of different embryonic origin to verify the presence of common genes characterizing the heterogeneity of cancer-associated fibroblasts. These automatically extracted biomarkers could be used to suggest appropriate therapies to inactivate the state of active fibroblasts, thus avoiding their action on tumor progression.

SUBMITTER: Esposito F

PROVIDER: S-EPMC7218276 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

Esposito Flavia F Boccarelli Angelina A Del Buono Nicoletta N

Bioinformatics and biology insights 20200508

The rapid development of high-performance technologies has greatly promoted studies of molecular oncology producing large amounts of data. Even if these data are publicly available, they need to be processed and studied to extract information useful to better understand mechanisms of pathogenesis of complex diseases, such as tumors. In this article, we illustrated a procedure for mining biologically meaningful biomarkers from microarray datasets of different tumor histotypes. The proposed method ...[more]

PMID: 32425511

Similar Datasets

Project description:BackgroundRegularly discarded lip tissue obtained from corrective surgeries to close the cleft lip represents an easily accessible and rich source for the isolation of primary fibroblasts. Primary fibroblasts have been described to show compelling similarities to mesenchymal stem cells (MSCs). Hence, cleft lip and palate (CLP) lip-derived fibroblasts could be thought as an intriguing cell source for personalized regenerative therapies in CLP-affected patients.MethodsInitially, we thoroughly characterized the fibroblastic nature of the lip-derived mesenchymal outgrowths by molecular and functional assays. Next, we compared their phenotype and genotype to that of bone marrow-mesenchymal stem cells (BM-MSCs) and of human lung-derived fibroblasts WI38, by assessing their morphology, surface marker expression, trilineage differentiation potential, colony-forming (CFU) capacity, and immunomodulation property. Finally, to better decipher the heterogeneity of our CLP cultures, we performed a single cell clonal analysis and tested expanded clones for surface marker expression, as well as osteogenic and CFU potential.ResultsWe identified intriguingly similar phenotypic and genotypic properties between CLP lip fibroblasts and BM-MSCs, which makes them distinct from WI38. Furthermore, our own data in combination with the complex anatomy of the lip tissue indicated heterogeneity in our CLP cultures. Using a clonal analysis, we discovered single cell-derived clones with increased levels of the MSC markers CD106 and CD146 and clones with variabilities in their commitment to differentiate into bone-forming cells and in their potential to form single cell-derived colonies. However, we were not able to gain clones possessing superior MSC-like capacities when compared to the heterogeneous parental CLP population. Additionally, all clones could still generate contractile forces and retained robust levels of the fibroblast specific marker FSP1, which was not detectable in BM-MSCs.ConclusionsOur results suggest that we isolate heterogeneous populations of fibroblasts from discarded CLP lip tissue, which show a prominently multipotent character in their entirety avoiding the need for elaborate subpopulation selections in vitro. These findings suggest that CLP lip fibroblasts might be a novel potential cell source for personalized regenerative medicine of clinical benefit for CLP patients.

Dataset Information

An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

Publications

An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets